Comparing Hitting Time Behavior of Markov Jump Processes and Their Diffusion Approximations. - Lukasz Szpruch; Desmond J. Higham (Multiscale Model. Simul., 2009)

Almost sure exponential stability of numerical solutions for stochastic delay differential equations. - Fuke Wu; Xuerong Mao; Lukasz Szpruch (Numerische Mathematik, 2010)

Strong convergence and stability of implicit numerical methods for stochastic differential equations with non-globally Lipschitz continuous coefficients. - Xuerong Mao; Lukasz Szpruch (J. Comput. Appl. Math., 2013)

First order strong approximations of scalar SDEs defined in a domain. - Andreas Neuenkirch; Lukasz Szpruch (Numerische Mathematik, 2014)

Martingale Functional Control variates via Deep Learning. - Marc Sabate Vidales; David Siska; Lukasz Szpruch (CoRR, 2018)

V-integrability, asymptotic stability and comparison property of explicit numerical schemes for non-linear SDEs. - Lukasz Szpruch; Xiling Zhang (Math. Comput., 2018)

Iterative Multilevel density estimation for McKean-Vlasov SDEs via projections. - Denis Belomestny; Lukasz Szpruch; Shuren Tan (CoRR, 2019)

An Adaptive Euler-Maruyama Scheme for Stochastic Differential Equations with Discontinuous Drift and its Convergence Analysis. - Andreas Neuenkirch; Michaela Szölgyenyi; Lukasz Szpruch (SIAM J. Numer. Anal., 2019)

Sig-SDEs model for quantitative finance. - Imanol Pérez Arribas; Cristopher Salvi; Lukasz Szpruch (ICAIF, 2020)

Conditional Sig-Wasserstein GANs for Time Series Generation. - Hao Ni 001; Lukasz Szpruch; Magnus Wiese; Shujian Liao; Baoren Xiao (CoRR, 2020)

Robust pricing and hedging via neural SDEs. - Patryk Gierjatowicz; Marc Sabate Vidales; David Siska; Lukasz Szpruch; Zan Zuric (CoRR, 2020)

Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. - Michael B. Giles; Mateusz B. Majka; Lukasz Szpruch; Sebastian J. Vollmer; Konstantinos C. Zygalakis (Stat. Comput., 2020)

Exponential Convergence and Stability of Howard's Policy Improvement Algorithm for Controlled Diffusions. - Bekzhan Kerimkulov; David Siska; Lukasz Szpruch (SIAM J. Control. Optim., 2020)

Sig-wasserstein GANs for time series generation. - Hao Ni 001; Lukasz Szpruch; Marc Sabate Vidales; Baoren Xiao; Magnus Wiese; Shujian Liao (ICAIF, 2021)

Identifiability in inverse reinforcement learning. - Haoyang Cao; Samuel N. Cohen; Lukasz Szpruch (NeurIPS, 2021)

Exploration-exploitation trade-off for continuous-time episodic reinforcement learning with linear-convex models. - Lukasz Szpruch; Tanut Treetanthiploet; Yufei Zhang 001 (CoRR, 2021)

Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime. - James-Michael Leahy; Bekzhan Kerimkulov; David Siska; Lukasz Szpruch (ICML, 2022)

Synthetic Data - what, why and how? - James Jordon; Lukasz Szpruch; Florimond Houssiau; Mirko Bottarelli; Giovanni Cherubin; Carsten Maple; Samuel N. Cohen; Adrian Weller (CoRR, 2022)

Optimal scheduling of entropy regulariser for continuous-time linear-quadratic reinforcement learning. - Lukasz Szpruch; Tanut Treetanthiploet; Yufei Zhang 001 (CoRR, 2022)

TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data. - Florimond Houssiau; James Jordon; Samuel N. Cohen; Owen Daniel; Andrew Elliott; James Geddes; Callum D. Mole; Camila Rangel Smith; Lukasz Szpruch (CoRR, 2022)

A Framework for Auditable Synthetic Data Generation. - Florimond Houssiau; Samuel N. Cohen; Lukasz Szpruch; Owen Daniel; Michaela G. Lawrence; Robin Mitra; Henry Wilde; Callum D. Mole (CoRR, 2022)

Inefficiency of CFMs: Hedging Perspective and Agent-Based Simulations. - Samuel N. Cohen; Marc Sabate Vidales; David Siska; Lukasz Szpruch (FC Workshops, 2023)

Mean-field Analysis of Generalization Errors. - Gholamali Aminian; Samuel N. Cohen; Lukasz Szpruch (CoRR, 2023)

Insurance pricing on price comparison websites via reinforcement learning. - Tanut Treetanthiploet; Yufei Zhang 001; Lukasz Szpruch; Isaac Bowers-Barnard; Henrietta Ridley; James Hickey; Chris Pearce (CoRR, 2023)

The AI Revolution: Opportunities and Challenges for the Finance Sector. - Carsten Maple; Lukasz Szpruch; Gregory Epiphaniou; Kalina Staykova; Simran Singh; William Penwarden; Yisi Wen; Zijian Wang; Jagdish Hariharan; Pavle Avramovic (CoRR, 2023)

A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces. - Bekzhan Kerimkulov; James-Michael Leahy; David Siska; Lukasz Szpruch; Yufei Zhang 001 (CoRR, 2023)

On the geometry of Stein variational gradient descent. - Andrew B. Duncan; Nikolas Nüsken; Lukasz Szpruch (J. Mach. Learn. Res., 2023)

Multi-index antithetic stochastic gradient algorithm. - Mateusz B. Majka; Marc Sabate Vidales; Lukasz Szpruch (Stat. Comput., 2023)

Generalization Error of Graph Neural Networks in the Mean-field Regime. - Gholamali Aminian; Yixuan He; Gesine Reinert; Lukasz Szpruch; Samuel N. Cohen (ICML, 2024)

Mirror Descent for Stochastic Control Problems with Measure-valued Controls. - Bekzhan Kerimkulov; David Siska; Lukasz Szpruch; Yufei Zhang 001 (CoRR, 2024)

Mirror Descent-Ascent for mean-field min-max problems. - Razvan-Andrei Lascu; Mateusz B. Majka; Lukasz Szpruch (CoRR, 2024)

ε-Policy Gradient for Online Pricing. - Lukasz Szpruch; Tanut Treetanthiploet; Yufei Zhang 001 (CoRR, 2024)

Numerical approximation of ergodic BSDEs using non linear Feynman-Kac formulas. - Emmanuel Gobet; Adrien Richou; Lukasz Szpruch (CoRR, 2024)

Understanding Transfer Learning via Mean-field Analysis. - Gholamali Aminian; Lukasz Szpruch; Samuel N. Cohen (CoRR, 2024)

Linear convergence of proximal descent schemes on the Wasserstein space. - Razvan-Andrei Lascu; Mateusz B. Majka; David Siska; Lukasz Szpruch (CoRR, 2024)

Gradient Flows for Regularized Stochastic Control Problems. - David Siska; Lukasz Szpruch (SIAM J. Control. Optim., 2024)

A Fisher-Rao gradient flow for entropic mean-field min-max games. - Razvan-Andrei Lascu; Mateusz B. Majka; Lukasz Szpruch (Trans. Mach. Learn. Res., 2024)

Optimal Scheduling of Entropy Regularizer for Continuous-Time Linear-Quadratic Reinforcement Learning. - Lukasz Szpruch; Tanut Treetanthiploet; Yufei Zhang 001 (SIAM J. Control. Optim., 2024)

Individualised Counterfactual Examples Using Conformal Prediction Intervals. - James M. Adams; Gesine Reinert; Lukasz Szpruch; Carsten Maple; Andrew Elliott (COPA, 2025)

PPO in the Fisher-Rao geometry. - Razvan-Andrei Lascu; David Siska; Lukasz Szpruch (CoRR, 2025)